AIMC Topic: Receptor, ErbB-2

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An exploratory study on predicting HER2-positive expression status of breast cancer using ultrasound radiomics combined with machine learning models.

PloS one
OBJECTIVE: This study aimed to investigate the feasibility and potential value of predictive models for human epidermal growth factor receptor 2 (HER2)-positive status in breast cancer (BC) based on radiomics features from conventional ultrasound ima...

Integrated Chemical Array and SERS Profiling of Plasma Small Extracellular Vesicles for Breast Cancer Diagnosis.

Nano letters
Small extracellular vesicles (sEVs) are nanoscale vesicles carrying biomolecules reflective of their cellular origin, making them attractive biomarkers for cancer diagnosis. In this study, we present a high-throughput strategy integrating amphiphile-...

Preoperative prediction of the HER2 status and prognosis of patients with endometrial cancer using multiparametric MRI-based radiomics: a multicenter study.

Scientific reports
Non-invasive preoperative assessment of HER2 status is critical for identifying candidates for targeted therapy and personalizing treatment strategies in endometrial cancer (EC). This study aims to assess the preoperative value of multiparametric mag...

Foundation model based multimodal transformer framework for survival analysis in HER2 stratified breast cancer.

Physics in medicine and biology
. To improve survival prediction for HER2-positive breast cancer by integrating histopathological, molecular, and clinical data using a multimodal transformer framework.. We propose a multimodal transformer framework for breast cancer survival predic...

Real-world data of CanAssist Breast- first immunohistochemistry and AI-based prognostic test.

Scientific reports
CanAssist Breast (CAB), an immunohistochemistry (IHC) and artificial intelligence-based prognostic test, was developed on Hormone receptor-positive (HR +), HER2/neu-negative (HER2-) breast tumors from Indian patients and validated in retrospective gl...

AI microscope facilitates accurate interpretation of HER2 immunohistochemical scores 0 and 1+ in invasive breast cancer.

Scientific reports
Accurate interpretation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) scores 0 and 1+ is crucial for treating HER2-low breast cancer patients with antibody-drug conjugates. To improve diagnostic precision, we developed...

Enhanced HER-2 prediction in breast cancer through synergistic integration of deep learning, ultrasound radiomics, and clinical data.

Scientific reports
This study integrates ultrasound Radiomics with clinical data to enhance the diagnostic accuracy of HER-2 expression status in breast cancer, aiming to provide more reliable treatment strategies for this aggressive disease. We included ultrasound ima...

Tuning antibody stability and function by rational designs of framework mutations.

mAbs
Artificial intelligence and machine learning models have been developed to engineer antibodies for specific recognition of antigens. These approaches, however, often focus on the antibody complementarity-determining region (CDR) whilst ignoring the i...

A computational study of cardiac glycosides from Vernonia amygdalina as PI3K inhibitors for targeting HER2 positive breast cancer.

Journal of computer-aided molecular design
The PI3K/Akt pathway plays a crucial role in regulating a broad network of proteins involved in the proliferation of HER2-positive breast cancer. The ethyl acetate fraction of Vernonia amygdalina, which contains cardiac glycosides, has been shown to ...

Multiomic integration reveals subtype-specific predictors of neoadjuvant treatment response in breast cancer.

Science advances
Neoadjuvant therapy has been widely used in breast cancer, but treatment response varies among individuals. We conducted multiomic profiling on tumor samples from 149 Chinese patients with breast cancer across ERHER2, ERHER2, and ERHER2 subtypes, cat...